#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time    : 2020/8/16 19:34
# @USER    : Shengji He
# @File    : FloodFill.py
# @Software: PyCharm
# @Version  : Python-
# @TASK:
from collections import deque
from typing import List


class Solution:
    def floodFill(self, image: List[List[int]], sr: int, sc: int, newColor: int) -> List[List[int]]:
        """
        An image is represented by a 2-D array of integers, each integer representing the pixel value of the
        image (from 0 to 65535).

        Given a coordinate (sr, sc) representing the starting pixel (row and column) of the flood fill, and
        a pixel value newColor, "flood fill" the image.

        To perform a "flood fill", consider the starting pixel, plus any pixels connected 4-directionally to the
        starting pixel of the same color as the starting pixel, plus any pixels connected 4-directionally to those
        pixels (also with the same color as the starting pixel), and so on. Replace the color of all of the
        aforementioned pixels with the newColor.

        At the end, return the modified image.

        Example 1:
            Input:
                image = [[1,1,1],[1,1,0],[1,0,1]]
                sr = 1, sc = 1, newColor = 2
            Output: [[2,2,2],[2,2,0],[2,0,1]]
            Explanation:
                From the center of the image (with position (sr, sc) = (1, 1)), all pixels connected
                by a path of the same color as the starting pixel are colored with the new color.
                Note the bottom corner is not colored 2, because it is not 4-directionally connected
                to the starting pixel.
        Note:
            - The length of image and image[0] will be in the range [1, 50].
            - The given starting pixel will satisfy 0 <= sr < image.length and 0 <= sc < image[0].length.
            - The value of each color in image[i][j] and newColor will be an integer in [0, 65535].

        :param image:
        :param sr:
        :param sc:
        :param newColor:
        :return:
        """
        # 广度优先搜索
        currColor = image[sr][sc]
        if currColor == newColor:
            return image
        rows, columns = len(image), len(image[0])
        que = deque([(sr, sc)])

        image[sr][sc] = newColor
        while que:
            x, y = que.popleft()
            for mx, my in [(x - 1, y), (x + 1, y), (x, y - 1), (x, y + 1)]:
                if 0 <= mx < rows and 0 <= my < columns and image[mx][my] == currColor:
                    que.append((mx, my))
                    image[mx][my] = newColor
        return image

    # 深度优先搜索
    def floodFill(self, image: List[List[int]], sr: int, sc: int, newColor: int) -> List[List[int]]:
        currColor = image[sr][sc]
        rows, columns = len(image), len(image[0])

        def dfs(x: int, y: int):
            if image[x][y] == currColor:
                image[x][y] = newColor
                for mx, my in [(x - 1, y), (x + 1, y), (x, y - 1), (x, y + 1)]:
                    if 0 <= mx < rows and 0 <= my < columns and image[mx][my] == currColor:
                        dfs(mx, my)

        if currColor != newColor:
            dfs(sr, sc)
        return image


if __name__ == '__main__':
    S = Solution()
    image = [[1, 1, 1], [1, 1, 0], [1, 0, 1]]
    sr = 1
    sc = 1
    newColor = 2
    print(S.floodFill(image, sr, sc, newColor))
    print('done')
